task_categories:
- text-generation
language:
- en
pretty_name: ArXiv Papers
ArXiv Papers
Description
ArXiv is an online open-access repository of over 2.4 million scholarly papers covering fields such as computer science, mathematics, physics, quantitative biology, economics, and more. When uploading papers, authors can choose from a variety of licenses. This dataset includes text from all papers uploaded under CC BY, CC BY-SA, and CC0 licenses through a three-step pipeline: first, the latex source files for openly licensed papers were downloaded from ArXiv’s bulk-access S3 bucket; next, the LATEXML conversion tool was used to convert these source files into a single HTML document; finally, the HTML was converted to plaintext using the Trafilatura HTML-processing library. Code for collecting, processing, and preparing this dataset is available in the common-pile GitHub repo.
Dataset Statistics
| Documents | UTF-8 GB |
|---|---|
| 321,336 | 21 |
License Issues
While we aim to produce datasets with completely accurate licensing information, license laundering and inaccurate metadata can cause us to erroneously assign the incorrect license to some documents (for further discussion of this limitation, please see our paper). If you believe you have found an instance of incorrect licensing in this dataset, please start a discussion on this repository.
Other Versions
This is the "raw" version of the ArXiv Papers dataset. If you are looking for the filtered version used to train Comma v0.1, you can find it here.
Citation
If you use this dataset, please cite:
@article{kandpal2025common,
title={{The Common Pile v0.1: An 8TB Dataset of Public Domain and Openly Licensed Text}},
author={Nikhil Kandpal and Brian Lester and Colin Raffel and Sebastian Majstorovic and Stella Biderman and Baber Abbasi and Luca Soldaini and Enrico Shippole and A. Feder Cooper and Aviya Skowron and Shayne Longpre and Lintang Sutawika and Alon Albalak and Zhenlin Xu and Guilherme Penedo and Loubna Ben and Elie Bakouch and John David and Honglu Fan and Dashiell Stander and Guangyu Song and Aaron Gokaslan and John Kirchenbauer and Tom Goldstein and Brian R and Bhavya Kailkhura and Tyler Murray},
journal={arXiv preprint},
year={2025}
}